Analysis of respiratory properties using the low-frequency piezoelectric sensor in patients undergoing intravenous sedation: A prospective observational study

Background

Patients who undergo general anesthesia may experience respiratory failure postoperatively because of respiratory depression or upper airway obstruction.

Aim

We investigated whether a piezoelectric sensor (AYA-P sensor) can be used to detect upper airway obstruction in patients undergoing intravenous sedation.

Methods

This prospective observational study included 26 patients who underwent dental treatment under sedation at a dental clinic. Participants were evaluated using a newly defined airway obstruction score (AOS). The AYA-P sensors were attached to the suprasternal notch and the midpoint between the umbilicus and xiphoid process. The patient's respiratory status was classified into four categories based on thoracic movements, capnography, and breathing sounds from recorded data (S1: no airflow, S2: hypoventilation, S3: normal breathing, and S4: artifact). The data obtained from the AYA-P sensors were processed using a 0.4-Hz low-pass filter, calculated using the moving standard deviation (MSD) method, and further processed using a 0.1-Hz low-pass filter (fMSD). Next, these data were differentiated (D-fMSD). We defined the positive predictive value (PPV) as fMSD or D-fMSD values higher than a threshold α in categories S1 and S2. PPV(αMAX) was defined as the maximum PPV, and the negative predictive value (NPV[αMAX]) was defined using the same αMAX.

Results

We compared each of the apnea-hypopnea time ratio (AHT%) and AOS with PPV(αMAX) and NPV(αMAX). The AHT% and AOS were correlated with PPV(αMAX) and NPV(αMAX) in the neck and abdomen, respectively. These findings suggest that an AYA-P sensor attached to the neck and abdomen can detect a patient's respiratory status.

Conclusion

Processed data obtained from AYA-P sensors can predict upper airway obstruction in patients, and the predicted data may be dependent on individual anatomical differences.

University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) clinical trial: Unique ID: UMIN000047007.

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